Apparatus and method for sensing rf signals from rf plasma processing equipment

ABSTRACT

A sensing device for monitoring electromagnetic radiation emanating from a plasma processing system. The sensing device may, for example, comprise at least two of a first probe for detecting a time varying RF electric field, a second probe for detecting a time varying RF magnetic field, and an optical probe for detecting the modulated light emission. The sensing device may, for example, further comprise a signal processing unit configured to receive a signal from each probe and to monitor the electromagnetic radiation with respect to only a single frequency of each signal.

FIELD

The present invention generally relates to the analysis of alternatingelectromagnetic fields from plasma systems at RF frequencies.

BACKGROUND OF THE INVENTION

Plasma processing of materials is ubiquitous in modern industrialmanufacturing industries. A common example is the etching and depositionof layers to form transistors during the manufacture of integratedcircuits in the semiconductor industry. Plasma processing is also usedin the manufacture of solar panels, flat panel displays, thin filmcoatings and medical devices—to name but a few.

Plasma is typically formed within a vacuum chamber. Once the air isevacuated, a gas recipe is added to the chamber at a chosen gaspressure. Energy is supplied to the vacuum chamber, usually electricalenergy, to excite the gas to the plasma state. The plasma state suppliesthe ions needed to modify the surface of the workpiece.

Electrical energy in the radio-frequency (RF) band is commonly used topower plasma reactors. The RF range is typically between tens ofkilohertz and hundreds of megahertz. Radio waves are coupled from an RFgenerator to the plasma chamber through the RF power delivery subsystemwhich includes a matching network to maximise power transfer. Power canbe coupled to the plasma in a number of different ways. In oneconfiguration, an RF powered electrode can be used to excite the plasmavia the electric field (E-field) formed between said powered electrodeand a counter electrode. The counter electrode may be another electrodeor the chamber vessel body, typically held at ground potential. When theE-field strength is sufficient, electrical breakdown occurs and theplasma is formed. RF current sustains the discharge and flows betweenthe powered electrode and ground. Electrons, stripped from their parentatoms and molecules, oscillate back and forward in the RF E-field,ionizing the background gas in the process thus sustaining the plasma.

In another configuration the RF power is coupled to the plasma through aRF antenna. The antenna does not need to be in direct contact with thebackground gas. RF current flowing through the antenna induces a timevarying magnetic field (H-field), perpendicular to direction of currentflow. The H-field is commonly coupled to the chamber through adielectric window. Once breakdown occurs, the H-field induces an E-fieldin the plasma which drives RF current. The free electrons oscillate inthe RF fields, ionizing the background gas, thus sustaining the plasma.Many other plasma reactor configurations and plasma generationmechanisms exist.

Regardless of the type of RF coupling mechanism, an interface regionbetween electrode or antenna and the plasma necessarily exists. Thisregion is called a plasma sheath. The sheath has a non-linear RFimpedance. Consequently, harmonics of the fundamental driving frequencyare excited. The plasma voltages and currents can have rich harmonicspectra as a result. The RF harmonic signature of the plasma process isdetermined by many variables including the fundamental plasmaparameters, the plasma chemistry, the chamber geometry, the chambersurface conditions and the mechanical characteristics of the chamber.The harmonic spectrum thus contains significant information about theplasma process health and performance.

As the plasma electrons oscillate in the RF fields they ionize and/orexcite the neutral gas particles. Electron impact excitation events areaccompanied by optical emission. Much of the light emitted comes fromthe visible region of the electromagnetic spectrum. The light emissionoccurs at specific wavelengths depending on the type of gas used. In RFplasmas the light emission intensity is modulated at the RF drivingfrequency and its higher harmonics by the electron motion.

In certain plasma reactor configurations there will be one or moredriving frequency. This generates a harmonic spectrum for eachfundamental driving frequency as well as intermodulation frequencies. Asensing apparatus to accurately measure the characteristics of thefrequency spectra generated in RF powered plasma reactors is highlydesirable. Accurately measured frequency/harmonic spectrum signaturescan be used to monitor process performance in real time.

The plasma processing system is often “leaky” to electromagnetic fields,due to its design. The RF time-varying electric and magnetic fieldsradiate through any non shielded or improperly grounded regions. Opticalemission radiates through any opaque regions such as viewports. Thisprovides three means of sensing RF spectra radiating from the plasmaprocessing system, using; a) a time-varying E-field sensor, b) a timevarying magnetic field (B-dot) sensor and c) a time varyinglight-intensity sensor.

The RF spectrum is typically presented as a signal amplitude versusfrequency graph. The signal amplitude may correspond to the time varyingE-field or B-field strength. The time varying optical signal amplitudewill correspond closely to the B-field strength, since both are drivenby the electron motion within the plasma system. These three signals areactually vector quantities with a phase component as well as amplitude.The phase angles between the fundamental and harmonic frequencies of theindividual spectra is a valuable dataset to measure because it isextremely sensitive to the changes in the electron motion within theplasma. Also, the phase relationships between corresponding frequencycomponents of the E-field and B-field spectra have been found to be verysensitive to certain physical phenomena in the plasma process. Throughthe processing and analysis of the sensed RF spectra, the plasma processcan be monitored in real time. To avoid the need for detailedcalibration of the measured RF spectra, statistical methods can be usedto baseline or fingerprint certain process conditions. This is typicallydone for known “healthy” processes. Subsequent processes, for the samesetpoints, can be compared against the baseline to check forstatistically significant changes. Gross changes will be easily detectedin a single data channel e.g. a sudden drop or rise in the E-fieldamplitude could signify a RF generator problem. Other changes may bemore nuanced and may require multivariate analysis using many datachannels from the RF spectra to detect them e.g. minor air leaks orslight wafer misplacement—nonetheless these issues can be detrimental tothe workpiece. Furthermore, some changes may only be detected in theadvanced data channels such as the phase measurements provided by thisinvention. For example the phase measurements can be very sensitive tocertain process endpoints e.g. when the etching of a layer iscompleted—even if that layer constitutes less than one percent of thesurface area of the workpiece.

E-field and B-dot probe pairs are commonly used in so-called VI sensorsfor measuring voltage and current flowing in transmission lines. Inpublication no. WO2014016357A2, a VI sensor apparatus is described. Thissensor is designed to be connected in series with the RF power feedline. For that reason it includes a section of transmission line, as isgenerally the case for this type of sensor. A broadband capacitivepick-up (E-field probe) is used to determine the voltage signal on theRF line connected to the plasma. An inductive loop (B-dot probe) is usedto determine the RF current in the RF line connected to the plasma. Thevoltage and current pick-ups are embedded in the RF transmission linesection of the VI sensor structure. The signal representing the currentand voltage are passed to an analog-to-digital converter (ADC), and thedigitised signals are processed in a field programmable gate array.While the inline VI sensor is a very important tool, it can be difficultto install without major modification to the plasma systemconfiguration.

In publication no. WO2018177965A1 an apparatus is described by McNallyet al in which a specially designed magnetic loop antenna is used tosense the plasma current flowing in the vicinity of a plasma chamberviewport from an external location. The antenna is carefully designedand calibrated. The output of the antenna is coupled to a spectrumanalyser to view the frequency spectrum detected by the antenna. Theinventors describe a frequency analysis technique to detect resonantfeatures on the plasma. The antenna operating in the isolated near fieldis critical for the correct functioning of this antenna. Shielding isused to prevent the antenna from detecting signals from matchingnetworks and other far field signal sources.

In publication no. WO2004006298A2 Parsons describes an invention thatutilises a RF antenna to sense RF radiation from a plasma systemremotely. The antenna can detect harmonic signals and is coupled to aprocessing unit for analysis. The processing unit is coupled to theplasma tool controller, where the sensed RF signals are used to adjustand maintain parameters of the plasma process based on the measuredsignal levels.

In publication no. US2007022766, Yamazawa et al describe an apparatusconsisting of two magnetic loop antennas, positioned inside the plane ofthe plasma chamber wall. The antennas are placed near the two electrodesof a capacitively coupled plasma reactor. Voltage signals generated bythe magnetic flux threading each loop are coupled to a signal processingunit. The current flowing out of the plasma to the chamber wall is thuscalculated.

In publication no. U.S. Pat. No. 6,441,620 B1, Scanlan et al describe amethod of fault identification in a plasma process using data from aninline VI sensor. For a given baseline plasma process, the changes inmagnitude of a plurality of Fourier components from said baseline, dueto changes in a plurality of process input parameters, are determined.These magnitude changes are stored as reference data. During anysubsequent production run, the plasma process is monitored for faultsand if one is found the baseline process is repeated with inputparameter values nominally the same as the original baseline values. Thechanges in the Fourier components from the original baseline values aredetermined and compared with the reference data. This comparison is usedto determine which of the plasma subsystems is most likely to havecaused the fault.

It is clear from the above that there are numerous shortcomings with theprior art. There is a need to address these shortcomings.

SUMMARY

There is disclosed herein a sensing device for monitoringelectromagnetic radiation emanating from a plasma processing systemcomprising at least two of (i) a first probe for detecting a timevarying RF electric field, (ii) a second probe for detecting a timevarying RF magnetic field and (iii) an optical probe for detecting themodulated light emission and the sensing device further comprising asignal processing unit configured to receive a signal from each probeand to monitor the electromagnetic radiation with respect to only asingle frequency of each signal.

The signal processing unit may be further configured to determine theamplitude of each signal from each probe to produce amplitude data.

The signal processing unit may be further configured to analyse theamplitude data to determine a changing average amplitude.

The signal processing unit may be further configured configured toidentify an event as corresponding to amplitude outside predeterminedlimits with respect to the average amplitude.

Optionally, the signal processing unit is further configured to storeamplitude data corresponding to the identified event.

Optionally, the signal processing unit is further configured to storeamplitude data for a predetermined time period corresponding to theidentified event.

The signal processing unit may be further configured configured todiscard amplitude data determined to not correspond to an identifiedevent.

The signal processing unit may be further configured to average theamplitude data of each signal over a predetermined time period.

Optionally, the signal processing unit is further configured to storethe averaged amplitude data corresponding to the predetermined timeperiod.

The signal processing unit may include an in-quadrature module and alocal oscillator, the in-quadrature module configured to multiply eachsignal from each probe by a signal from the local oscillator in order toselect the single frequency.

The signal processing unit may include a phase lock loop configured totune the local oscillator so that it tracks each signal from each probebetween a lower and upper frequency limit.

The signal processing unit further may include a filter and averagingmodule configured to convert the output signals from the in-quadraturemodule to average values and remove modulation from the output signalsto produce the a signal vector for each signal.

The signal processing unit may further include a vectoring block,configured to phase rotate the signal vectors in unison to produce avoltage signal vector on the real axis and having zero phase.

Optionally, he signal processing unit further includes a first in firstout buffer configured to store the signal vectors after processing bythe vectoring block.

Optionally when the plasma process is pulsed the signal processing unitis configured to analyse amplitude data with respect to at least one ofthe signals and store parameters of a pulse based on the amplitude data.

BRIEF DESCRIPTION OF THE DRAWINGS

The present application will now be described with reference to theaccompanying drawings in which:

FIG. 1 illustrates a plasma processing system showing the variousregions where electrical and optical electromagnetic emission can bedetected;

FIG. 2 shows a sensing device in accordance with present teachingwherein the individual sensing elements in a single module;

FIG. 3 shows a sensing device in accordance with present teachingwherein the individual sensing elements are distributed about a plasmaprocessing system;

FIG. 4 shows the sensing device of FIG. 2 with co-located sensingelements in more detail;

FIG. 5(a) illustrates the flow of data from the ADC to the memory of thesensing device when operating in a high speed detection mode;

FIG. 5(b) shows the logic for an FPGA of the sensing device whenoperating in the high speed detection mode;

FIG. 6 shows an illustration of a fault score spectral fingerprint thatcan be produced using the sensing device in accordance with the presentteachings;

FIG. 7 shows an illustration of fault score monitoring of a chambercleaning that can be produced using the sensing device in accordancewith the present teachings;

FIG. 8 shows a chart illustrating an example of low open area end-pointdetection using the sensing device in accordance with the presentteachings;

FIG. 9 shows a number of charts illustrating how the sensing device inaccordance with the present teachings can detect pressure, gas flow andgas concentrations in a plasma processing system;

FIG. 10 shows a number of charts illustrating how the sensing device inaccordance with the present teachings can detect a displaced waferwithin a plasma processing system;

FIG. 11 shows a number of charts illustrating how the sensing device inaccordance with the present teachings allows the detection of an arcwithin a plasma process; and

FIG. 12 shows a chart illustrating how the sensing device in accordancewith the present teachings allows the detection of a pulse within aplasma process.

DETAILED DESCRIPTION OF THE DRAWINGS

There is provided by present teachings an apparatus/device and methodfor sensing electromagnetic signals radiating from a plasma processingsystem, processing the sensed data in the form of RF spectra andanalysing said spectra to detect statistically significant plasmaprocess changes to identify fault conditions.

The sensor of the sensing device may comprise two or more of thefollowing three sensing elements; a first probe to sense the timevarying electric field, a second probe to sense the time varyingmagnetic field and an optical probe(e.g., a high frequency photodiode)to detect the RF modulated light emission. The second probe and theoptical probe sense the RF current flow within the plasma system. Thefirst probe can be used with one of the other two to detect phasechanges between the two fields. When measured simultaneously andsynchronously it enables the determination of the phase angle betweenelectric and magnetic field spectral components. That is, the sensingdevice in accordance with the present teachings samples signalssynchronously in such a way as to preserve the phase data betweenfrequencies and harmonics between the signals. This phase measurement isespecially sensitive to RF impedance changes of the plasma. The sensingdevice also includes a signal processing unit. This unit is designed tomonitor the phase angle between the fundamental frequency and itsharmonics for each individual spectra. These phase measurements areespecially sensitive to changes in chemistry within the plasma.

In the present teachings, a remote E-field and B-Dot probe may be usedto detect the RF fields emitted from the plasma system. A photodiode orother optical sensor can be added for extra sensitivity. Henceforth,this three element sensor in accordance with the present teachings maybe referred to as a VIO sensor. The specific configuration(s) of the VIOsensor in accordance with the present teachings will be describedhereinafter.

it should be appreciated that while the terms B-Dot probe and E-fieldprobe are used herein these terms are no intended to limit the sensingdevice to ‘perfect’ B-Dot probes that only measure changes along the Baxis or ‘perfect’ E-field probes that only measure changes along the Eaxis. In practice, the sensing device of the present teachings functionswith probes that don't align with the E or B axis as long as the probesare sufficiently independent on the electromagnetic field plane. In thepresent teachings each probe is susceptible to some amount of the otherfield i.e., the E-field probe detects the time varying RF magnetic fieldand the B-Dot probe detects the time varying RF electric field. Theprobes of the present teachings could be more generally described as twodifferent electromagnetic field probes, each lying in a different vectorplane to the other.

One of the three VIO sensor signals is chosen as the reference to whichthe others are synchronised for phase measurements. The optimumconfiguration uses the E-field as reference to which the B-field and/oroptical RF spectra are synchronised. However, any signal from any of thethree probes can be chosen. The reason for synchronisation is to allowdetermination of the phase relationship between corresponding frequencycomponents of the E-field spectra, B-field spectra and RF spectra.

The phase of the B-field RF frequency components relative to thecorresponding E-field RF frequency components is related to the chambergeometry and its mechanical structure. The phase of the optical RFfrequency components relative to the corresponding E-field RF frequencycomponents is sensitive to the gas chemistry rather than the geometry.Electrons oscillating in the electric fields excite the gas atoms to ahigher energy state. The atom will stay in the excited state for someperiod of time. When the excited electron decays back to the groundstate, a photon of light is emitted. The time between the excitation ofthe atom and its subsequent return to ground state is seen as a phaseshift between the optical RF frequency components and the correspondingelectric field frequency components. For this reason it is important tomeasure both the RF magnetic field and RF optical signal phase shiftsfor maximum insight into the health and performance of the plasmaprocess.

In modern plasma tools, view port sizes are miniaturised and RFshielding is added to minimise RF leakage through the viewport. RFshielding is often more effective for blocking E-field leakage, but notas effective for B-field leakage. Optical RF emission is unimpeded by RFshielding as long as a line of sight to the internal chamber isavailable. While the optical detector always needs a viewport, there aremany regions of the plasma system where the electrical RF signals can bedetected remotely, as illustrated in FIG. 1. Examples of regions of aplasma processing system where radiated RF signals can be detectedinclude but are not limited to:

(101) the coaxial transmission line between an RF generator and amatching network (unit); whether in-line or through the ground shield(or with an area of shielding removed)

(102) inside the match unit/circuit, at the housing wall for example

(103) outside the match unit, through the cooling fan

(104) through the RF housing between the match unit and plasmas chamber(a slot may be required)

(105) through the turbo pump

(106) inside an ICP source region, at the housing wall for example

(107) inside the plasma chamber

Given that multiple difference locations in a plasma processing systemcan be chosen for monitoring electromagnetic radiation, the sensor ofthe sensing device in accordance with the present teachings has twopreferred physical configurations. In one configuration the sensingelements are co-located in an “antenna” module. The E-field probe, theB-dot probe and the high frequency photodiode are co-located within themodule or housing. This module is ideal for mounting at a largerviewport where two or all three signals can be detected simultaneously.This configuration is illustrated in FIG. 2. This shows the sensor 200in accordance with the present teachings within the module 201. Themodule 201 is located at a viewport 204 of the plasma processing system100.

FIG. 2 also shows the sensor 200 connected to a signal processing unit202 via a signal coupling cable as will be explained in more detailhereinafter. The combination of the sensor 200 and signal processingunit may be considered to be a sensing device.

In another configuration, the individual sensing elements of the sensor200 are distributed to different regions of the plasma processing system100 where they can be best exposed to the radiated signals that they aresensitive to. This configuration is illustrated in FIG. 3. In thisexample, the optical detector/sensor 301 is located at the view port (oroptical fibre port), the B-Dot sensor 302 is mounted inside the ICPplasma source housing and the E-field probe 303 is either mounted on theinternal wall of the match box or inline with the coaxial cable betweengenerator and match box. When installed between the generator and matchunit, the E-field probe 303 is exposed to significantly lower harmonicsignal levels since they are heavily attenuated by the matching unit.Nonetheless, with a sufficiently sensitive signal processing unit 202, astable E-field reference can be obtained to allow accurate measurementof the phase changes in the B-Dot and/or optical RF spectra (if theE-field is chosen as the reference).

The B-dot probe 302 comprises of an inductive pickup loop with multiplewindings. The time varying magnetic flux threading the loop induces avoltage across the loop output. The loop voltage is coupled to a signalconditioning circuit (also referred to herein as a frequency responselevelling circuit herein). The signal conditioning circuit is used toregulate the output voltage of the inductive loop such that magneticfluxes of equal amplitude, across a wide frequency range, induce equalor similar voltage levels at the output of the signal conditioningcircuit.

The E-field probe 303 comprises of a capacitive pickup. The time varyingelectric field charges the capacitor and induces a voltage across it.The output of the capacitive pickup is coupled to another signalconditioning circuit (frequency response levelling circuit) to achievethe same frequency levelling effect described with respect to the B-dotprobe. The signal conditioning circuit is used to regulate the outputvoltage of the capacitive pickup such that electrical fluxes of equalamplitude, across a wide frequency range, induce equal or similarvoltage levels at the output of the signal conditioning circuit.

The optical detector 301 may be a photodiode. The light intensityreaching the photosensitive area of the optical detector induces avoltage at the output. The optical detector 301 is typically sensitiveto light in the 200 nm to 1000 nm wavelength range but other ranges canalso be used as necessary. The detector is designed to have a flatresponse to light of the same intensity across a range of wavelengths,within the optical bandwidth specified. In other words the voltagegenerated at the output of the optical detector is approximately equalfor different wavelengths with the same intensity. The optical detectorhas a high frequency bandwidth. This means that the optical detectoroutput can respond to the time varying light intensity in the 10's kHzto 100's MHz frequency range and is designed to have a flat frequencyresponse in a similar way to the B-dot and E-field sensors. Keeping theresponse of the sensors regulated across the frequency range of interestprevents issues like saturation due to resonance effects at certainfrequencies.

Turning to FIG. 4, this illustrates the remote, non invasive sensingdevice in accordance with the present teachings with co-located sensingelements as well as the signal processing unit. That is, FIG. 4 showsthe internal configuration of the sensing device i.e., the sensor 201and signal processing unit 202 of FIG. 2.

The sensing elements (optical sensor 301, E-field sensor 303 and B-dotprobe 302) and the frequency response levelling circuits 401, 402 403make up the analog front end of the VIO sensor in accordance with thepresent teachings. Each levelling circuit outputs an analog voltagesignal proportional to the quantity sensed by the respective sensingelement 301, 302, 303. The analog voltage output is an alternatingcurrent (AC) signal in the RF band. To extract the frequency spectra ina form that can be analysed and visualised in a useful way, a signalprocessing unit 202 is incorporated in the VIO sensing device.Individual co-axial cables (which can be bundled in a common sheath)carry the AC signals to the signal processing unit 202. A multi-channelADC is used to sample the signals from each of the sensing elements. Thereference signal (such as the E-field sensor but any one of the sensorcan be chosen as a reference), is coupled to channel one of the ADC. Theother two channels are synchronised with said channel one. It should beappreciated that the chosen reference signal can be fixed e.g., it isalways the signal from the E-field sensor or the signal processing unitcan dynamical chose the reference signal using each measurement orsensing procedure. The strongest or highest intensity signal may bechosen or some other criteria may be used by the signal processing unitto choose the reference signal. Any suitable criteria may be chosen bythe person skilled in the art.

The high speed ADCs sample the AC waveforms generated by the analogfront end. Data sampling is carried out simultaneously or synchronouslyon all channels. The sampling is done synchronously in such a way as topreserve the phase data between frequencies and harmonics between thetwo signals. The skilled person can choose the appropriate componentsand specific technique(s) for ensuring the phase data and harmonics arepreserved as appropriate. A data block of 512 samples is typicallyrecorded as a first step. The block size is chosen arbitrarily and canbe varied to meet different requirements. The data block is transferredto a field programmable gate array (FPGA) where a fast Fourier transform(FFT) is carried out. The FFT transforms the time domain AC waveforminto a frequency spectrum. The frequency spectra are sent to amicroprocessor (not shown) of the signal processing unit for storage andfurther processing, including averaging. Multiple FFTs are averagedtogether to reduce the signal-to-noise ratio. The averaging alsopreserves channel phase information.

In the present teachings, the AC waveforms are sampled asynchronouslyfrom block to block but synchronously from channel to channel i.e.sampling does not commence at the same point in the AC period each timea new waveform is recorded on any one channel, but sampling occurs onall channels at precisely the same time. As a result, the phase,relative to zero degrees, of the fundamental frequency component and itsharmonics varies with each new FFT processed. In order to performaveraging, a phase rotation operation is carried out. The fundamentalfrequency component of the first ADC channel is chosen as the reference.The phase of the complex fundamental frequency component is rotated to apredetermined phase angle ϕ. The phase shift Δϕ used to rotate thecomplex fundamental frequency component from its measured value to thepredetermined value is recorded. The complex fundamental frequencycomponents off all the individual ADC channels are also rotated by Δϕ.All harmonic frequency components (N) are rotated by N×Δϕ, where Ndenotes the harmonic number such that N=1 is the first harmonic or thefundamental frequency. This serves the dual purpose of aligning each FFTin phase space to enable averaging across consecutive samples, whilealso preserving the phase relationship between harmonics within theindividual spectra and the phase relationship between correspondingfrequency components of spectra from different ADC channels.

After the preconfigured number of averages has been completed, thesignal processing unit 202 outputs the dataset to a user for viewing andfurther analysis. That is, the dataset may be output, in the form of aresults table, by the sensing device to external computer resources suchas a PC. However, further analysis may also be done (on-board) by thesensing device.

The dataset or results table contains the frequency of each signalfundamental, the magnitude of each signal, the phase of each signalrelative to the chosen reference signal, the magnitude of each signalharmonic, each signal harmonics phase relative to its correspondingharmonic on the reference signal, and the phase of the reference signalsharmonics relative to the reference signals fundamental for each signal.

The below exemplary results tables correspond to two signalsrespectfully—signal frequency 1 and signal frequency 2. These tablesillustrate that for more than one signal the results table for the firstsignal is essentially duplicated for any further signals (signalfrequencies).

TABLE 1 Signal Frequency 1 EM1 Sensor EM2 Sensor Optical 1 SensorHarmonic 1 Fundamental Magnitude 0 Magnitude Phase wrt EM1 H1 MagnitudePhase wrt EM1 H1 Harmonic 2 Frequency Magnitude Phase wrt H1 MagnitudePhase wrt EM1 H2 Magnitude Phase wrt EM1 H2 Harmonic 3 Magnitude Phasewrt H1 Magnitude Phase wrt EM1 H3 Magnitude Phase wrt EM1 H3 Harmonic 4Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H4 Magnitude Phase wrtEM1 H4 Harmonic 5 Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H5Magnitude Phase wrt EM1 H5 Harmonic 6 Magnitude Phase wrt H1 MagnitudePhase wrt EM1 H6 Magnitude Phase wrt EM1 H6 Harmonic 7 Magnitude Phasewrt H1 Magnitude Phase wrt EM1 H7 Magnitude Phase wrt EM1 H7 Harmonic 8Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H8 Magnitude Phase wrtEM1 H8 Harmonic 9 Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H9Magnitude Phase wrt EM1 H9 Harmonic 10 Magnitude Phase wrt H1 MagnitudePhase wrt EM1 H10 Magnitude Phase wrt EM1 H10 Harmonic 11 MagnitudePhase wrt H1 Magnitude Phase wrt EM1 H11 Magnitude Phase wrt EM1 H11Harmonic 12 Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H12 MagnitudePhase wrt EM1 H12 Harmonic 13 Magnitude Phase wrt H1 Magnitude Phase wrtEM1 H13 Magnitude Phase wrt EM1 H13 Hermonic 14 Magnitude Phase wrt H1Magnitude Phase wrt EM1 H14 Magnitude Phase wrt EM1 H14 Harmonic 15Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H15 Magnitude Phase wrtEM1 H15

TABLE 2 Signal Frequency 2 EM1 Sensor EM2 Sensor Optical 1 SensorFundamental Magnitude 0 Magnitude Phase wrt EM1 H1 Magnitude Phase wrtEM1 H1 Frequency Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H2Magnitude Phase wrt EM1 H2 Magnitude Phase wrt H1 Magnitude Phase wrtEM1 H3 Magnitude Phase wrt EM1 H3 Magnitude Phase wrt H1 Magnitude Phasewrt EM1 H4 Magnitude Phase wrt EM1 H4 Magnitude Phase wrt H1 MagnitudePhase wrt EM1 H5 Magnitude Phase wrt EM1 H5 Magnitude Phase wrt H1Magnitude Phase wrt EM1 H6 Magnitude Phase wrt EM1 H6 Magnitude Phasewrt H1 Magnitude Phase wrt EM1 H7 Magnitude Phase wrt EM1 H7 MagnitudePhase wrt H1 Magnitude Phase wrt EM1 H8 Magnitude Phase wrt EM1 H8Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H9 Magnitude Phase wrtEM1 H9 Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H10 MagnitudePhase wrt EM1 H10 Magnitude Phase wrt H1 Magnitude Phase wrt EM1 H11Magnitude Phase wrt EM1 H11 Magnitude Phase wrt H1 Magnitude Phase wrtEM1 H12 Magnitude Phase wrt EM1 H12 Magnitude Phase wrt H1 MagnitudePhase wrt EM1 H13 Magnitude Phase wrt EM1 H13 Magnitude Phase wrt H1Magnitude Phase wrt EM1 H14 Magnitude Phase wrt EM1 H14 Magnitude Phasewrt H1 Magnitude Phase wrt EM1 H15 Magnitude Phase wrt EM1 H15

When outputting the data, amplitude and phase information for eachfrequency component of each sensor channel is reported. Typically, thephase difference between the relevant frequency components is calculatedand output to the user. The signal processing unit is designed to becapable of processing multiple fundamental frequency componentssimultaneously. This is particularly useful when monitoring plasmaprocesses powered by more than one frequency. The signal processing unitcan typically output a full data set at selectable speeds in the rangefrom approximately 1 millisecond to 1 second, depending on theapplication requirements.

Not all RF plasma processes operate in continuous wave (CW) mode. Someare pulsed at frequencies in range for a few hertz to tens of kilohertz.For this reason, the signal processing unit 202 may have a built inexternal synchronization port. The unit 202 accepts a (TTL) signal inputfrom the pulsed RF generator of the plasma processing system. A boxcar(averaging) technique enables RF waveform capture at specific timesduring the pulsed RF period. In this scenario, averaging is carried outover multiple pulses. This technique can be used to build up the averagepulse profile with one microsecond resolution if required. Apart fromthe synchronization, the signal processing is carried out in the sameway. The pulsed RF signal may have one or multiple power levels duringthe repetition cycle, but once a TTL synchronisation signal is availablethe signal processing unit can carry out the analysis unimpeded.

In recent years, pulsed RF plasma processes have been developed suchthat the fundamental carrier frequency is dynamic rather than fixed.This enables greater control over power matching throughout the pulseperiod, where mechanical movement of the match positions at the speedrequired is not practical. Typically, a dynamic range of +/−10% aroundthe carrier frequency is sufficient. The signal processing unit inaccordance with the present teaching is also dynamic carrier frequencyenabled, for continuous wave and pulsed RF process monitoring. A smartFFT process tracks carrier frequency movement in the frequency binsadjacent to where the fundamental frequency is expected to appear. Thus,the spectrum of the carrier frequency can be obtained at any pointwithin its+/−10% dynamic tuning range.

Another signal processing method may be used by the sensing device(sensor and signal processing unit) in accordance with the presentteachings for high speed event monitoring. The aforementioned frequencyspectrum analysis requires sampling of a complex waveform and furtherFFT processing. The FFT is a relatively slow process. Hence, aroot-mean-square (RMS) detection technique, with a narrow pass-bandfilter to isolate the fundamental frequency may be used. It should beappreciated that the sensing device in accordance with the presentteachings is capable of operating in two modes—(i) the above describedfrequency spectrum mode and (i) a high speed detection mode describedhereinafter.

In the high speed detection mode, the root mean square (RMS) amplitudeof each data channel can be determined in real-time at high speed(typical report rates of one microsecond or less) and high speedamplitude data captured. This high speed method does not allow forharmonic spectrum measurement. However, the real-time, high speedprocessing enables pulse profile monitoring without the need forsynchronisation with a TTL signal. Individual pulse profiles can becaptured and analysed compared with the aforementioned averaged pulseprofiles obtained in the boxcar technique. Important pulsecharacteristics such as duty cycle, pulse repetition frequency etc. canbe established on a per pulse basis to build up defect or faultcorrelation metrics. Pulse profile monitoring is just one type of highspeed measurement that the high speed detection method can be used for.Another important type of high speed event is the RF arc. Arcs arecommon in industrial plasma processing chambers and occur for a myriadof reasons. A common type is the micro-arc. Dielectric particles formnano layers on the chamber walls for example. When the outer surface ofthe layer charges up to a certain level, electrical breakdown of thelayer occurs. The arc burns through the layer to reach the grounded wallbehind. As it does so, particles are emitted from the surface which canpose a major risk to the wafer being processed. These arcs cause asudden sharp change in the plasma voltage and current. The severity ofthe change can be categorised in terms of the length of time it lastsand the relative change in voltage or current level induced. It is veryimportant to measure the onset of micro-arcing as this may often be theprelude to a major or catastrophic arc event which would cause damage tothe processing tool. The signal processing unit, operated in the highspeed detection mode, is ideally suited to detecting such micro-arcingevents.

In addition, the high-speed mode provides full “time coverage” of thesignals from the sensors/probes. Known methods use a block technique,which monitors portions of time in the signal akin to looking though apicket fence, it is possible to see what's behind without getting 100%coverage. That is, the prior art relies on discrete sampling while thepresent teachings provide continuous monitoring. It is important forevent detection to have 100% time coverage of the signal so that eventsare not missed. That is, the continuous monitoring of an entire plasmaprocess can be provided and amplitude data is obtained for the entireprocess. The signal processing unit is configured to continuouslydetermine the amplitude of each signal from each probe to (continuously)produce amplitude data.

FIG. 5(a) shows the flow of data from ADC to memory with respect to thehigh speed mode of operation. This all happens inside the VIO sensingdevice and is performed by a combination of the FPGA and on-board CPUwithin the signal processing unit 202. In this exemplary embodiment, allhigh speed amplitude data is transferred in blocks from FPGA to CPU withresolution of one microsecond. That is, high speed amplitude data istransferred from the pre-processed data memory 501 to the eventdetection and classification module 502, the pulse measurement module503 and data averaging module 504 of the CPU. The CPU checks for eventsand stores up to 5 ms of data locally in RAM (Event Data Memory 505) foreach detected event. It will be appreciated that any length of time canbe chosen as appropriate and 5 ms is merely an example. The eventdetection technique uses a moving (changing) average to compare the mostrecent value against. In the exemplary embodiment, the moving average issimply the average of the last 1000 values, i.e. the last 1 ms. An eventis classified as corresponding to an amplitude outside user definedlimits with respect to the moving average.

The CPU also averages the measured RMS signal level and stores theaveraged data every 100 ms (in Context Data Memory 506). Again thechoice of 100 ms is arbitrary and any time period can be chosen. This“context” average is different to the aforementioned moving average andin the exemplary embodiment is an average of points in each 100 msblock.

The CPU checks for arc and RF pulse events, storing arc and/or pulsesnapshots for each event in the event data memory 505. That is, the CPUprocesses all data in the first in, first out buffer (FIFO) 509 andstores only data which corresponds to an event in the event data memory.The average “context” data is stored (i.e. 1 data point every 100 ms) sothat the signal processing unit records the average rms values.

With respect to the pulse (profile) measurement module 503, it provideshigh resolution captures of out of specification pulses for storage inthe event data memory 505. The pulse measurement module 503 providespulse statistics every 100 ms. (i.e., period, duty cycle, average “on”values, max and min “on” values) to the context data memory.

Software running on a connected PC may retrieve the data from thesensor's event data memory and context data memory and store it to fileson a connected PC.

It should be appreciated that the signal processing unit does not haveto capture and store both event data and context data. Only one theseprocesses could be performed according to user requirements. However,capturing the context data with the event data is advantageous. Havingthe “context” data provides a way to determine what else was going on atthe time an event occurs, i.e. did an event happen just after the powerwas applied. Was voltage and current different than normal before andafter the event (relative to a previously run plasma process).

How the high speed amplitude data, stored in memory 501, is captured andprocessed using the ADCs 506, RMS detectors 507 and the filter andaveraging block 508 is outlined in more detail with respect to FIG.5(b).

The sensing device may also be provided with a communication interface.This can be used to stream the data to external computing resources(e.g., a PC). The interface also allows the computing resources torequest the data rather than having it streamed.

The block diagram shown in FIG. 5(b) illustrates the FPGA logic used forthe aforementioned high speed (RMS). The FPGA logic shown in FIG. 5(b)used for RMS detection is very different to the logic used for harmonicspectrum detection (spectrum mode). It will be appreciated that theconfiguration described herein is merely exemplary and the personskilled in the art may use alternative logic configuration in order toachieve the same high speed detection mode of the sensing device inaccordance with the present teachings.

With respect to FIG. 5(b), the signal process unit of the sensing devicein the high speed mode tracks only one fundamental frequency, anddetermines the amplitude and phase of the sensor signals at an updaterate of one microsecond or faster. This data is stored in a first in,first out (FIFO) buffer 509 ready for retrieval by the CPU. The CPUinterface allows the FPGA registers to be memory mapped in the CPUsmemory space. The CPU sets up direct memory access (DMA) transfers fromthe FPGA's FIFO directly to memory.

The RMS FPGA logic has two clock domains, one relates to the ADC clocksampling rate, while the other clock domain relates to the CPUinterface. The high level diagram shown in FIG. 5(b) illustrates thesignal path from the ADC 506 to FIFO memory 509. An in-quadrature (IQ)block 510 multiplies the V, I or O signal (signals from the individualsensing elements) by a local oscillator signal, which effectivelyselects the frequency to monitor.

A phase lock loop (PLL) control logic 511 is used to tune the localoscillator so that it tracks incoming signals, between a lower and upperfrequency limit. The filter and averaging block 508 converts theinstantaneous IQ signals to average values. The IQ output will containthe “DC” signal required, plus a modulation signal related to thesampling frequency and the signal frequency. The filters and averaginglogic 508 remove the modulation from the IQ output signals to producethe VIO signal vectors. The VIO signal vectors are then passed to avectoring block 512 every microsecond, where the VIO signal vectors arephase rotated in unison such that the V signal is real i.e., the vectorwill lie on the real axis and have zero phase. Then V as well as I_(r)and I; and/or O_(r) and O_(i) (where subscripts r and i denote the realand imaginary component respectively) are stored in the FIFO 509 readyfor the CPU of the signal processing unit to read.

The person skilled in the art will appreciate that the high speed (RMS)detection technique described herein is not limited to the VIO sensingdevice of the present teachings but can also be used with known priorart sensors such as the aforementioned VI sensor device or any sensorwhich can supply the appropriate signals. All of the signal (V, I, andO) are not required for this high speed detection technique.

While the VIO remote sensing device in accordance with the presentteachings can be calibrated to give absolute measurements of theE-field, B-dot field and modulated light intensities, it is notessential for the type of application described herein. In the followingdescription, a method for baselining a known healthy process ispresented, which relies on relative signal intensities only. Anacceptable process window is established using a sequence of processruns from known healthy processes. The healthy process window follows anormal distribution for the measured variables. The baselining processinvolves the measurement of a sample of the distribution for allvariables. To establish if a new process run is within the acceptableprocess window, a statistical method is used. To facilitate thestatistical analysis, a database is employed where each measurement istime stamped and stored for later retrieval. This statistical analysiscan be done on-board or on an external computer.

One example of the baselining sequence requires the calculation of themean (μ) and standard deviation (s), for each variable, for the chosensample size (n). These parameters are stored in memory. The distancefrom the mean, measured in standard deviations, can be determined foreach new measurement. Other methods can also be used.

Individual variables may not be sensitive to certain types of processvariance. Each frequency spectrum can include 15 harmonic amplitudesalong with 15 associated phases for each fundamental frequency. With 3ADC data channels and with the inter-spectra phase parameters, hundredsof variables are obtained in each measurement. Therefore, amulti-variable model is implemented for optimum sensitivity. Theapproach, using distance from the mean analysis, is just one method ofmany that can be used to establish deviations within a multivariate dataset, when compared against a baseline sample. Principal componentanalysis techniques and neural networks may also be used. Derivatives ofthe measured datasets can also be used to further improve sensitivity.

With the large number of variables that the VIO sensing device iscapable of producing, it can sometimes be useful to include only themost sensitive variables in the calculation for optimum sensitivity.Alternatively, all measured variables can be included. A spectralfingerprint is shown in FIG. 6. In this example, a plasma processingchamber was baselined before a set of 5 wafers were run through theprocessing chamber sequentially. The X-axis shows the spectral componentnumber such that 1-15 are the E-field amplitudes of the fundamentalfrequency and 14 subsequent harmonics, 16-30 are the B-dot amplitudesfor the same frequency components and 31-45 are the phase angles betweenthe channels for each frequency component. Element 46 in this spectrumis the result of the multivariate distance from the mean calculation foreach wafer. The calculated values are approximately one standarddeviation for all 5 wafers, indicating that the process was in a healthystate throughout. To prevent false-alarms a threshold can be implementede.g. only a distance from the mean above 6 sigma would be considered afault (fault score).

The spectrum shown in FIG. 6 has 45 spectral components (and the resultof the fault score calculation). Including the optical RF spectrum wouldbring the number of spectral components to 75. Furthermore, adding theharmonic phase measurements, relative to their fundamental frequency,adds another 14 spectral components for each live data channel. Thisprovides a dataset that is highly sensitive to the majority of faultsthat can be experienced during plasma processing. The fault score methodprovides a relatively simple fault detection technique where a largedata set is condensed into a single fault score with a statisticalsignificance. However, it is possible that different faults can returnthe same score. In the event that a classification of the fault isrequired, a more sophisticated approach is required. For faultclassification, spectral pattern recognition techniques can be used suchthat an intelligent algorithm can be trained to recognise specific faultsignatures or fingerprints.

The sensing device and methodology described heretofore can be used todetect various process faults and events including:

a) Chamber wall condition

-   -   b) Process end-points    -   c) Malfunctioning pressure control valves, gas flow problems,        leaks    -   d) Wafer displacement    -   e) RF Arc events    -   f) Atypical RF pulse events

The techniques described herein can be performed by the sensing deviceof by an external computer connected to the sensing device and using thedata from the sensing device.

It should be noted that e) and f) categories above do not require thesame baselining process described earlier. The chamber wall condition isan important consideration for many plasma processes. During the etchingor deposition of material in wafer manufacturing, layers are formed onthe chamber walls. These layers, especially if non-conducting, canchange the plasma impedance significantly. This can change the plasmaproperties and push the process conditions beyond the acceptable processwindow. The process can be baselined using the method described earlier,when the chamber walls are known to be clean. When the chamber wallsreach a predetermined level of contamination, a chamber clean process isperformed. Accurate feedback on when the chamber is adequately clean ishighly desirable. FIG. 7 shows the calculated fault score for thechamber during the cleaning process. A score of 2a was determined to berepresentative of an adequately clean chamber. This technique is used toalert the user when the chamber has reached a clean state. For theexample shown in FIG. 7, the chamber reached a clean state afterapproximately 800 seconds.

Plasma processing often involves multiple etch and deposition steps tocreate features and structures on the substrate surface. The etch stepusually requires that one layer of a material is removed completely toexpose the underlying material. The etch process duration must be chosencarefully to ensure the features are created within dimensionalspecification tolerances. If the etch process does not run for longenough, the layer will be under-etched i.e. the layer is not fullyremoved to expose the layer underneath. If the etch process is run fortoo long the layer will be over-etched i.e. the layer underneath can bedamaged when the layer of interest is removed fully but the etchingprocess continues. The term etch end-point is used to define the pointin time when the etching process has fully removed the layer ofinterest. Just after the layer is removed fully, the plasma process willstart to etch the material underneath. Optical emission spectroscopy(OES) techniques are often used to monitor the plasma composition andlook for the presence of particles from the underlying material. Oncethese particles are detected it can be assumed that the etching of thelayer of interest is complete and the process can be terminatedcorrectly. For very low foreign particle concentrations, OES does notalways work. It has been shown that fault score techniques using the VIOsensing device in accordance with the present teachings can be moresensitive to low open area etch end-points compared to OES techniques.FIG. 8 shows an etch end-point example. The process was baselined usingdata from the beginning of the process. It was established that a 4 ascore was the optimum time to terminate the process. The RF harmonicspectrum, especially the harmonic phase components (relative to thefundamental), is highly sensitive to small changes in the plasmachemistry seen at the etch end-point. The change in plasma compositiondue to the new material entering the process can be detected to very lowlevels using the RF spectra and the T-score method already described.The optical RF spectrum detector of the current invention should not beconfused with the standard OES technique mentioned. In the presentinvention, a high frequency-bandwidth photodiode is used to capture theRF spectrum by measuring the modulation of the light intensity. Astandard OES system monitors the time-averaged light intensity emittedfrom the plasma process and breaks it up into a spectrum of opticalwavelengths. Specific wavelengths are used to identify different atomicor molecular species. Therefore, OES is useful for determining thechemical composition of a plasma process. However, at low speciesconcentrations the resolution limit becomes a problem.

Many plasma processing chambers are operated under vacuum. The chamberpressure is tightly regulated. Gas flow and gas concentrations are alsotightly controlled. A fault with the pressure and/or gas control systemscan have catastrophic consequences for the substrate being processed. Totest the sensitivity of the sensing device in accordance with thepresent teachings to detection of gas flow issues, a control experimentwas carried out in a plasma processing chamber running a silane plasmafor silicon deposition applications. A baseline spectrum was recorded.The silane concentration was increased by 10% and decreased by 10%relative to the baseline condition while keeping all other parametersconstant. A RF fingerprint was recorded for both conditions. Thefingerprint fault score space for a 45 channel RF spectrum is shown inFIG. 9. Channel 46 shows the multivariate fault score result. There areclear differences in the spectral fingerprint and the fault score isgreater than 5a in both cases, making the change in silane concentrationeasily detectable. Much lower concentration variations are detectableacross a wide range of plasma gas chemistries.

Wafer positioning on the pedestal (or electrostatic chuck) of a plasmaprocessing device is critically important for wafer processing. Thereare several reasons why a wafer may be displaced on the chuck. The robotarm can malfunction and place it in the incorrect position. Morecommonly, debris from other parts of the tool can fall on the chuck suchthat a wafer placed thereon can be elevated off the chuck surface.Regardless of the cause, an undetected wafer displacement can lead tothe wafer being incorrectly processed and scrapped down the line. Thedisplacement of a wafer impacts the plasma impedance and the resultingharmonic spectra. FIG. 10 illustrates the impact on the B-dot fieldmeasured remotely using the VIO sensor apparatus. The main chart shows aplot of the fundamental B-dot field magnitude versus time during theplasma process. Data for six correctly placed wafers is shown along withdata for a displaced wafer. The processing of the displaced wafer wascut short. The inset in FIG. 10 also shows the harmonic spectra of theE-field and B-dot signals for both correctly placed and displacedwafers. The difference is very clear in this example, without the needfor statistical analysis. Nonetheless, this example demonstrated thecapability of the VIO sensing device in accordance with the presentteachings to detect misplaced wafers to prevent wafer scrap events.

As previously mentioned, when the central signal processing module isconfigured for high speed (RMS) detection, short-lived (RF) events canbe detected remotely. FIG. 11 shows an example of such an event, an arc,being detected in a plasma process. In particular, FIG. 11 shows a topgraph illustrates the presence of an arc within a typical plasmaprocess. The bottom graph of FIG. 11 shows a high definition view of thearc with one microsecond resolution

It will be appreciated that the VIO sensing device described hereinprovides a non-invasive method for RF plasma arc detection. Earlydetection of arcing in a plasma processing chamber is highly desirableas it can avoid product scrappage if remedial action is taken. The arcsignature is present in the E-field signal, the B-dot signal and theoptical RF signal. Therefore, one or all sensing elements can be used toremotely detect arcs at various locations around the plasma system asillustrated in FIG. 3.

Pulsed RF plasma processes are used extensively for advancedsemiconductor node manufacturing. Pulsing the plasma provides access todifferent plasma chemistries not attainable in continuous wave RF mode.These plasmas are typically pulsed in the few hertz to tens of kilohertzfrequency range. Achieving highly repeatable plasma conditions, frompulse to pulse, is essential for process yield. To achieve saidrepeatable plasma conditions the variance of the pulse characteristicsmust remain within certain thresholds. The number of wafer defects areknown to be correlated with pulse variations for example. The high speed(RMS) detection mode of the VIO sensing device is ideally suited toanalysing each pulse profile to extract the key pulse characteristicse.g. pulse repetition frequency, duty cycle, pulse-on time etc. Thesignal processing unit (pulse profile measurement module 503) may sampleincoming data signals every microsecond (of course other time frames arepossible). This provides a detailed snapshot of each pulse profilewithin the pulsed frequency range of interest. Each pulse profile isanalysed in real-time and the important pulse parameters are stored. Thepulse profile with one microsecond samples is discarded if it fallswithin the user configured tolerance limits. On the other hand, if thepulse is out of tolerance the high definition pulse profile is storedfor further analysis. This “exception” based approach limits the amountof data produced i.e. only high definition profiles are stored for thepulses that do not meet the tolerance criteria. FIG. 12 illustrates apulse profile captured by the B-dot sensor of the VIO sensing device inaccordance with the present teachings. This was an atypical pulse inwhich the duty cycle was diagnosed to be outside of the acceptabletolerance range. Specially, FIG. 12 provides an example of single pulseprofile capture with one microsecond resolution over a five millisecondwindow.

It should be appreciated that the statistical analysis and processing ofthe detected data or RF spectra described with respect to FIGS. 6 to 12above can be done locally on the sensing device of the present teachingsor remotely at computing resources (e.g., a PC) connected to the sensingdevice.

In view of the above, it will be appreciated that the present teachingsprovide a device and method for sensing RF signals radiating from aplasma processing system, processing said signals in the form of RFspectra, analysing said spectra to determine a plurality of amplitudeand phase components and carrying out of statistical analysis toidentify fault states of the said plasma processing system based onvariations of the amplitude and phase components.

The sensor of the sensing device is comprised of an E-field probe, B-dotprobe and/or optical RF detector. The E-field probe (or any of theprobes) may be used as a reference for the other probes and is used tosense the time varying electric field.

The B-dot probe and optical RF detector are used to sense the timevarying electron motion or the plasma current within the reactor. Theindividual probes may be co-located or distributed at suitable locationsaround the plasma system.

Unlike prior art designs, the sensing apparatus is not coupled tospectrum analyzer or network analyzer. These analyzers are expensive andcumbersome to use. Also, they do not enable the advanced detectionfeatures required. Instead, a signal processing unit is used. The signalprocessing unit provides new information related to the remotely sensedRF spectra that has not been reported in prior art remote RF plasmasensor designs. Novel measurements are; a) harmonic phase, phase betweenspectra from different sensors, spectral analysis in pulsed RF andfrequency tuning plasma processes, RMS detection of arcs and RMSdetection of individual pulsed RF profiles. A statistical method isdescribed based on spectral fingerprinting of known “healthy” plasmaprocess conditions. Variations in the phase and amplitude of thespectral components are analysed and a fault score is attributed to eachnew process measurement. Thresholds can thus be configured to alert theuser to detected process faults. The phase measurements are particularlysensitive to small changes in plasma chemistry and plasma impedance. Theability to measure phase, as described, makes the sensing device of thepresent teachings a very useful diagnostic tool for detection of subtleprocess changes that occur during low open area endpointing, forexample, where standard technology is now falling short.

There is provides herein three means of sensing RF spectra radiatingfrom the plasma processing system, using; a) a time-varying E-fieldsensor, b) a time varying magnetic field sensor and c) a time varyinglight-intensity sensor. The sensing device in accordance with thepresent teachings provides mon-invasive sensing of the radiated RFspectra through these three mechanisms, or pairs thereof, simultaneouslyand synchronously, which provides extra data channels not provided byprior art designs.

The invention is not limited to the embodiment(s) described herein butcan be amended or modified without departing from the scope of thepresent invention.

1. A sensing device for monitoring electromagnetic radiation emanatingfrom a plasma processing system comprising at least two of: (i) a firstprobe for detecting a time varying RF electric field; (ii) a secondprobe for detecting a time varying RF magnetic field; and (iii) anoptical probe for detecting the modulated light emission; and thesensing device further comprising: a signal processing unit configuredto receive a signal from each probe and to monitor the electromagneticradiation with respect to only a single frequency of each signal.
 2. Thesensing device of claim 1 wherein the signal processing unit is furtherconfigured to continuously determine the amplitude of each signal fromeach probe to produce amplitude data.
 3. The sensing device of claim 2wherein the signal processing unit is further configured to analyse theamplitude data to determine a changing average amplitude.
 4. The sensingdevice of claim 3 wherein the signal processing unit is furtherconfigured to identify an event as corresponding to amplitude outsidepredetermined limits with respect to the average amplitude.
 5. Thesensing device of claim 4 wherein the signal processing unit is furtherconfigured to store amplitude data corresponding to the identifiedevent.
 6. The sensing device of claim 5 wherein the signal processingunit is further configured to store amplitude data for a predeterminedtime period corresponding to the identified event.
 7. The sensing deviceof claim 6 wherein the signal processing unit is further configured todiscard amplitude data determined to not correspond to an identifiedevent.
 8. The sensing device of claim 2 wherein the signal processingunit is further configured to average the amplitude data of each signalover a predetermined time period.
 9. The sensing device of claim 8wherein the signal processing unit is further configured to store theaveraged amplitude data corresponding to the predetermined time period.10. The sensing device of claim 1 wherein the signal processing unitincludes an in-quadrature module and a local oscillator, thein-quadrature module configured to multiply each signal from each probeby a signal from the local oscillator in order to select the singlefrequency.
 11. The sensing device of claim 10 wherein the signalprocessing unit includes a phase lock loop configured to tune the localoscillator so that it tracks each signal from each probe between a lowerand upper frequency limit.
 12. The sensing device of claim 10 whereinthe signal processing unit further includes a filter and averagingmodule configured to convert the output signals from the in-quadraturemodule to average values and remove modulation from the output signalsto produce a signal vector for each signal.
 13. The sensing device ofclaim 12 wherein the signal processing unit further includes a vectoringblock, configured to phase rotate the signal vectors in unison toproduce a voltage signal vector on the real axis and having zero phase.14. The sensing device of claim 13 wherein the signal processing unitfurther includes a first in first out buffer configured to store thesignal vectors after processing by the vectoring block.
 15. The sensingdevice of claim 1 wherein when the plasma process is pulsed the signalprocessing unit is configured to analyse amplitude data with respect toat least one of the signals and store parameters of a pulse based on theamplitude data.
 16. The sensing device of claim 3 wherein the signalprocessing unit is further configured to average the amplitude data ofeach signal over a predetermined time period.
 17. The sensing device ofclaim 4 wherein the signal processing unit is further configured toaverage the amplitude data of each signal over a predetermined timeperiod.
 18. The sensing device of claim 5 wherein the signal processingunit is further configured to average the amplitude data of each signalover a predetermined time period.
 19. The sensing device of claim 6wherein the signal processing unit is further configured to average theamplitude data of each signal over a predetermined time period.
 20. Thesensing device of claim 7 wherein the signal processing unit is furtherconfigured to average the amplitude data of each signal over apredetermined time period.